Techniques for Evaluating Clustering R package Clustering version 1.7.10 The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided. See Martos, L.A.P., García-Vico, Á.M., González, P. et al.(2023) <doi:10.1007/s13748-022-00294-2> "Clustering: an R library to facilitate the analysis and comparison of cluster algorithms.", Martos, L.A.P., García-Vico, Á.M., González, P. et al. "A Multiclustering Evolutionary Hyperrectangle-Based Algorithm" <doi:10.1007/s44196-023-00341-3> and L.A.P., García-Vico, Á.M., González, P. et al. "An Evolutionary Fuzzy System for Multiclustering in Data Streaming" <doi:10.1016/j.procs.2023.12.058>. Software Depends: R (>= 3.5.0) Imports: amap, apcluster, cluster, ClusterR, data.table, dplyr, foreach, future, ggplot2, gmp, methods, pracma, pvclust, shiny, sqldf, stats, tools, utils, xtable, toOrdinal Suggests: DT, shinyalert, shinyFiles, shinyjs, shinythemes, shinyWidgets, tidyverse, shinycssloaders Luis Alfonso Perez Martos <lapm0001@gmail.com> Comprehensive R Archive Network (CRAN) Luis Alfonso Perez Martos [aut, cre] (<https://orcid.org/0000-0002-5154-6105>) GPL (>= 2) 2024-04-22 application/tgz https://CRAN.R-project.org/package=Clustering doi:10.32614/CRAN.package.Clustering